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VERIFIEDBy Xavier Rivera· ·1 min read

Nvidia AI Ports 3,000-Cell GPU Library Overnight

Nvidia uses reinforcement learning in NVCell to port its 2,500-3,000 cell GPU library to new nodes overnight on one GPU, beating human timelines. This speeds next-gen GPU development amid surging AI chip demands.

Source:PC Gamer
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Nvidia AI Ports 3,000-Cell GPU Library Overnight
TL;DRAI · 60 sec read

Nvidia ports a 3,000-cell GPU standard cell library overnight using NVCell AI on one A100 GPU, cutting time from 80 person-months previously needed by eight engineers for TSMC nodes. Designs match or exceed human results in cell size, power, and delay. Nvidia applies AI to floorplanning via reinforcement learning and verification.

Nvidia slashes standard cell library porting from 80 person-months to overnight on one A100 GPU. Bill Dally, Nvidia's chief scientist, reveals this during a GTC session with Google's Jeff Dean, as reported by PC Gamer.

The library holds 2,500 to 3,000 pre-designed cells for GPU components like texture units. Previously, eight engineers spent 10 months adapting it to new TSMC process nodes. Nvidia's NVCell tool, now at version 2 or 3, generates designs that match or exceed human results in cell size, power, and delay.

NVCell builds on years of development, with Dally offering updated cell counts. Nvidia also deploys AI for floorplanning via prefix reinforcement learning, tackling placement challenges. Its F model, an executable GPU representation shared with TSMC, targets verification bottlenecks in design.
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